Current architectures for scalable and universal photonic quantum computing live on two extremes.
The first type leverages the impressive scalability of continuous-variable (CV) entangled resource states to implement computation on discrete-variable (DV) information (specifically, qubits) encoded in bosonic modes [1]}, [2]}.
While the type of CV resource required for this first approach can be produced deterministically and scalably, these architectures require DV resources also to be generated on-demand and deterministically, which imposes infeasible hardware requirements.
The second type of architectures involves generating entangled resource states made entirely out of the bosonic qubits themselves [3]}, [4]}, [5]}, [6]}, [7]}.
Resources that exclusively comprise high-quality bosonic qubits are endowed with a degree of resilience to noise, but are more difficult to make, as either the scalable generation of the qubits or the operations required to combine them into larger states are probabilistic.
In light of this, it is important to devise a scheme that combines the best of both worlds: using CV resources to ease the burden on the preparation of bosonic qubits, but retaining a sufficiently high concentration of bosonic qubits to ensure low-noise operations whenever the CV modes are consumed.
Here we present such a scheme and analyze how the robustness to error depends on the relative concentration of bosonic qubits in the entangled resource state.
